1. Field of the Invention
The present invention relates to a person tracking method, a person tracking apparatus and a person tracking program storage medium which track movements of a person whose image is captured by a camera.
2. Description of the Related Art
A person tracking method includes two kinds of processing which are: person detection processing for detecting a person to start tracking, and person tracking processing for focusing on a feature of the detected person thereby tracking the person. In the person detection processing, the person is detected by finding a difference between the person and a background or a temporal difference (see Japanese Patent Application Publications No. 2000-105835 and No. 2002-342762), or by focusing on a certain feature of the person and determining whether the feature is present or not. In the person tracking processing, tracking processing that employs a Kalman filter or the like is generally performed.
Further, there has been proposed an attempt to obtain and hold information representing a correspondence between a two-dimensional moving image and a three-dimensional real space, and then convert the position of a measured object on the two-dimensional image into that in the three-dimensional real space and reconvert the position into that on the two-dimensional image after predicting the position in the three-dimensional real space, thereby precisely predicting a movement of the object on the two-dimensional image (Japanese Patent Application Publication No. H8-94320).
In such a conventional method however, there is a problem as described below.
The method of detecting a person by a differential operation using a background-based difference, a temporal difference or the like relies on a factor such as a temporal change of the background or an image. Therefore, when the background or the like is complicated, a precise background image or the like cannot be created, resulting in deterioration of a detection capability.
Meanwhile, in the tracking processing using the Kalman filter or the like, calculation complexity is great and thus a long processing time is required. Moreover, in order to make the Kalman filter or the like operate properly, a high frame rate is required, which places an additional burden on the processing.
Further, in order to obtain the information representing the correspondence between the two-dimensional moving image and the three-dimensional real space, for example, it is necessary to make an advance preparation by carrying out actual measurement and the like and thus, the method is practically difficult.